User presence prediction driven device management

Patent metadata

Field	Value
Publication number	US-11593166-B2
Application number	US-201916724875-A
Country	US
Kind code	B2
Filing date	Dec 23, 2019
Priority date	Feb 19, 2016
Publication date	Feb 28, 2023
Grant date	Feb 28, 2023

Abstract

Pooling computing resources based on inferences about a plurality of hardware devices. The method includes identifying inference information about the plurality of devices. The method further includes based on the inference information optimizing resource usage of the plurality of hardware devices.

First claim

What is claimed is:

1. A method of managing a hardware resource of a computing device, the method comprising:
receiving, at the computing device, a request to consume the hardware resource from the computing device for execution of a task;
in response to receiving the request, determining, based on a usage model associated with the computing device, that access to functionality of the hardware resource of the computing device is to be lost after a period of time, the usage model containing records of one or more usage patterns of the computing device; and
in response to determining that access to the functionality of the hardware resource of the computing device is to be lost after the period of time, prioritizing the execution of the task at the computing device over other tasks to be executed at the computing device before access to the functionality of the hardware resource of the computing device is lost.

2. The method of claim 1 , further comprising:
identifying, based on the usage model, another computing device that is proximate to the computing device; and
offloading, from the computing device, the execution of the task to the other computing device.

3. The method of claim 1 , further comprising:
identifying, based on the usage model, another period of time after which the computing device has access to another computing device;
determining whether the other period of time is within a predetermined threshold;
in response to determining that the other period of time is within the predetermined threshold,
preventing execution of the task at the computing device; and
upon elapse of the other period of time, offloading, from the computing device, the execution of the task to the other computing device.

4. The method of claim 1 , wherein the hardware resource includes at least one of processor cycles, network bandwidths, memory capacity, or storage capacity.

5. The method of claim 1 , wherein the one or more usage patterns include records individually containing data representing a time, a location, and one or more activities performed at the time and the location by the computing device and another computing device.

6. The method of claim 1 , further comprising selecting one of the one or more usage patterns based on a time or a location at which the request is received.

7. The method of claim 1 , further comprising:
in response to determining that access to the functionality of the hardware resource of the computing device is to be lost after the period of time,
determining, based on the usage model, whether the computing device and another computing device are proximate to each other such that a user has access to both the computing device and the other computing device; and
in response to determining that the computing device and the other computing device are proximate to each other such that the user has access to both the computing device and the other computing device, executing the task using the hardware resource from both the computing device and the other computing device.

8. A server for managing a hardware resource of a computing device, the server comprising:
a processor; and
a memory operatively coupled to the processor, the memory having instructions executable by the processor to cause the server to:
upon receiving a request to consume the hardware resource of the computing device for execution of a task, determine, based on a usage model associated with the computing device, that access to functionality of the hardware resource of the computing device is to be lost after a period of time, the usage model containing records of one or more usage patterns of the computing device; and
in response to determining that access to the functionality of the hardware resource of the computing device is to be lost after the period of time, prioritize the execution of the task at the computing device over other tasks to be executed at the computing device before access to the functionality of the hardware resource of the computing device is lost.

9. The server of claim 8 , wherein the hardware resource includes at least one of processor cycles, network bandwidths, memory capacity, or storage capacity.

10. The server of claim 8 , wherein the one or more usage patterns include records individually containing data representing a time, a location, and one or more activities performed at the time and the location by the computing device.

11. The server of claim 8 , wherein the memory includes additional instructions executable by the processor to cause the server to:
identify, based on the usage model, another computing device that is accessible to the computing device; and
offload, from the computing device, the execution of the task to the other computing device.

12. The server of claim 11 , wherein the memory includes additional instructions executable by the processor to cause the server to select one of the one or more usage patterns based on a time or a location at which the request is received and utilize the selected usage pattern to determine whether a user has access to the other computing device.

13. The server of claim 8 , wherein the memory includes additional instructions executable by the processor to cause the server to:
determine, based on the usage model, that the computing device is to lose access to another computing device after the period of time; and
instruct the other computing device to prevent additional tasks from being offloaded to the computing device.

14. The server of claim 8 , wherein the memory includes additional instructions executable by the processor to cause the server to:
determine, based on the usage model, whether the computing device and another computing device are proximate to each other such that a user has access to both the computing device and the other computing device; and
in response to determining that the computing device and the other computing device are proximate to each other such that the user has access to both the computing device and the other computing device, execute the task using the hardware resource from both the computing device and the other computing device.

15. A method of managing a hardware resource of a first computing device and a second computing device, the method comprising:
receiving, at the first computing device, a request to consume the hardware resource for execution of a task;
in response to receiving the request, determining, based on a usage model associated with the first computing device and the second computing device, that the first computing device has access to the second computing device for a period of time, the usage model containing records of one or more usage patterns of both the first computing device and the second computing device;
in response to determining that the first computing device has access to the second computing device for the period of time,
delaying execution of the task at the first computing device; and
offloading, from the first computing device to the second computing device, the execution of the task thereby avoiding consumption of the hardware resource by the first computing device during the period of time.

16. The method of claim 15 , wherein the hardware resource includes at least one of processor cycles, network bandwidths, memory capacity, or storage capacity.

17. The method of claim 15 , further comprising selecting one of the one or more usage patterns based on a time or a location at which the request is received and using the selected usage pattern to determine whether a user has access to the second computing

Assignees

• Microsoft Technology Licensing Llc

Inventors

• Kishan Arun U
• Wilson Emily Nicole
• Soliman Mohammed Nashaat
• Maisuria Paresh
• Weinberg Shira
• Virdi Gurpreet
• Brown Jared

Classifications

• G06N5/043

  Distributed expert systems; Blackboards · CPC title

• G06F9/5005 Primary

  to service a request · CPC title

• G06F2209/502

  Proximity · CPC title

• G06F9/5094

  where the allocation takes into account power or heat criteria (power management in computers in general G06F1/3203; thermal management in computers in general G06F1/206) · CPC title

• G06F2209/509

  Offload · CPC title